• JEP: General paper on temporal explanations

    It may require some effortful thinking and some background knowledge to construct a plausible explanation from scratch, so you need a good reason to do so. One of the most important reasons for why people generate explanations is to resolve inconsistencies. Previous research showed as much: when faced with some inconsistent causal information, reasoners spontaneously… Continue reading

  • 📄 Now in Psych Review: Computational model of 200+ reasoning problems

    Phil Johnson-Laird and I have a new paper the describes a theory and computational model of how people reason about properties. The theory holds that people construct small-scale mental simulations of entities linked to their properties, and that the more mental simulations they build, the harder a problem will be. A computer model, mReasoner, simulates… Continue reading

  • 📄 Cognitive Science paper on reasoning about desires

    Hillary Harner and I have a new theoretical paper out in Cognitive Science on the processes and mental representations people rely on to reason about desire. The paper shows that people think of desires as “counterfactive” — A wants X implies that X isn’t the case by default. It also shows that people separate desires… Continue reading

  • 💬 Interview with Künstliche Intelligenze

    I was recently interviewed by Nina Bonderup Dohn and Marco Ragni at KI – Künstliche Intelligenz, a German journal of artificial intelligence. You can check out that interview here. Continue reading

  • 📄 New paper on recursion out in PBR

    Phil Johnson-Laird, along with his collaborators Monica Bucciarelli, Robert Mackiewicz, and myself, published a paper in Psychonomic Bulletin & Review that reviewed research into how humans consciously reason about recursive operations. Though the term “recursion” is often used by computer scientists to describe specific types of programs, people without any background or training in computer science can… Continue reading

  • 🎉 Congrats to Reasoning Lab alumni Hillary Harner and Laura Kelly!

    Hillary Harner and Laura Kelly successfully completed their NRC Postdoctoral Fellowships this Fall — congratulations to them both! Throughout their years at NRL, Laura and Hillary made some important discoveries into how people reason about durations and how they reason about desire. Laura Kelly‘s work in the Reasoning Lab focused on how people reason about… Continue reading

  • 👋🏽 Branden Bio starts his postdoc at NRL!

    I’m extremely excited that Branden Bio began his postdoc at NRL this week! Dr. Bio is coming from Princeton’s Psychology Department, where he worked on studying attention, awareness, and its underlying neural mechanisms. His recent work focuses on how people attribute conscious states to others. He’s published papers in PNAS, eLife, and Cerebral Cortex. At… Continue reading

  • 🎞 ICYMI: CogSci 2021 presentations on time, desire, quantity

    At this year’s CogSci 2021, the Reasoning Lab presented recent work, including: Laura Kelly’s research on how people build explanations to resolve inconsistencies in temporal premises (paper, video) Hillary Harner’s work on how they distinguish between desires and intentions (paper, video) Gordon Briggs and Hillary Harner’s work on preferences in people’s quantified descriptions of groups… Continue reading

  • 🎞 Recent work by the R Lab at ICT 2021

    The Reasoning Lab presented work on how people think and reason about time, durations, causality, bouletics, kinematics, and quantifiers at this year’s International Conference on Thinking 2021. For those who couldn’t make the conference, I’ve included an archive of the presentations here: 🎞 Directional biases in durative inference presented by Laura Kelly 🎞 The consistency… Continue reading

  • 📃 mReasoner reasoning engine detailed in Psych Review

    Phil Johnson-Laird and I recently published a deep dive into the mReasoner computational cognitive model and the new theory of reasoning about properties that it implements. We describe a new model based theory of reasoning about quantifiers, such as “all”, “some”, and “most”, as well as a series of simulation studies that show how the… Continue reading